Multiobjective Optimization of Medium-Frequency Transformers for Isolated Soft-Switching Converters Using a Genetic Algorithm

The main challenge of medium-frequency transformers is the number of design parameters, constraints and objectives, and the difficulty of handling them on a particular design. This paper presents a novel computer-aided optimal design for MF transformers using a multiobjective genetic algorithm, in particular the nondominated sorting genetic algorithm II. The proposed methodology has the aim of reaching the best MF transformer for a given power converter topology, by optimizing transformer efficiency, weight, and also, transformer leakage and magnetizing inductances at the same time. The proposed methodology and the optimal solutions are validated with the design and the development of two 10-kVA/500-V transformers considering two different topologies. Finally, some experimental measurements are presented so as to demonstrate the proposed models and the performance of built transformers.